OBJECTIVES: Distributional cost-effectiveness analyses evaluate equity and effectiveness of interventions; inequality aversion (IA) is a crucial parameter representing the trade-off between reducing health inequality and total population health gains. A United Kingdom survey elicited a general population IA parameter using questions on participants’ demographics and health attitudes, animated instructional video, and quantitative benefit trade-off (BTO) instrument requiring graph comprehension. Adaptation requires a rigorous process to ensure relevance to existing disparities and the local healthcare system. Our objective was to adapt the survey for the United States.

METHODS: We used a systematic, multi-phased approach to adapt the survey for the US context. First, we engaged an international working group with contemporary experience on similar instruments to provide feedback on participant comprehension, video instruction, and general suitability. Second, we reviewed the literature to identify US-specific data for the BTO instrument and health attitudes questions. Third, we pre-tested the survey to evaluate participant comprehension quantitatively-demanding BTO. Fourth, we pilot-tested the survey to assess completion and logical response rates.

RESULTS: Working group input informed adaptations to: tailor the animated video’s themes and script for the US setting; develop a second instructional video to improve participants’ comprehension of the BTO. We used US quality-adjusted life expectancy data to modify the BTO instrument. Aligning questions on health attitudes with existing US national surveys allowed for sample benchmarking. Iterative rounds of pretesting resulted in re-phrasing of survey items for clarity, inclusion of screener questions related to graph comprehension and graph interpretation checks preceding the BTO.

CONCLUSIONS: Modifications of the quantitatively demanding BTO instrument were designed to increase task comprehension and probability of survey completion. Specifically, use of an additional instructional video on the BTO exercise, a screener for graph comprehension, and a BTO comprehension check are effective to increase the proportion of logical responses to be used for IA analysis.